7–9 Apr 2011
Europe/Stockholm timezone

Contribution List

33 out of 33 displayed
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  1. Prof. Vincent Blondel (University of Louvain)
    07/04/2011, 10:20
    Many complex networks have their nodes distributed in space. In this talk, I will describe various recent results for spatially distributed networks. In particular, I will report results obtained from a community detection method on a large network constructed from communications between millions of mobile phone users at a country level. I will quantify in this network the decrease with...
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  2. Dr Jari Saramäki (Aalto University)
    07/04/2011, 11:00
    In temporal networks, where nodes are connected through sequences of temporary events, information or resources can only flow through paths that follow their time-ordering. The properties of these temporal paths play a crucial role in dynamic processes: consider, e.g., simple SI spreading dynamics, whose speed is determined by the time it takes to complete such paths. I will discuss...
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  3. Dr Renaud Lambiotte (FUNDP)
    07/04/2011, 11:40
    Social science aims at understanding how large-scale behaviour emerges from the intrinsic properties of a large number of individuals and their pairwise interactions. Contrary to network connectivity, whose organization has been explored in email or mobile phone data, the psychological profile of large-scale populations has not been studied so far. In this work, we have analyzed...
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  4. Prof. Erik Sonnhammer (Stockholm University)
    07/04/2011, 13:40
    Interactomes computationally predicted via data integration are becoming an increasingly popular tool and context for biological research. However merging disparate data sources and presenting relevant parts of a global network is not trivial. FunCoup, an optimised Bayesian framework and a web resource, was developed to resolve these issues. FunCoup provides a number of uniqe features....
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  5. Dr Sebastian Bernhardsson (Niels Bohr Institute)
    07/04/2011, 14:10
    The metabolism of an organism makes up a very well defined network of reactions catalyzed by enzymes. These highly complex networks has presumably evolved from a simple primordial metabolism, from where they have diversified and specialized under the constraints of an underlying biochemistry. But how diverse are these networks? How much do they have in common, what can an ensemble of...
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  6. Dr Yong-Yeol Ahn (Northeastern University)
    07/04/2011, 14:50
    Animals, especially omnivores, feed selectively to fulfill energy needs and nutrient requirements, guided by chemical cues perceived as flavors. Among animals, humans exhibit the most diverse array of culinary practice. The diversity raises the question whether there are any general patterns of ingredient combination that transcend individual tastes and cuisines. We introduce a flavor...
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  7. Dr Kwang-Il Goh (Korea University)
    07/04/2011, 15:20
    Persistent recurrence of global economic crises throughout economic history calls for understanding of their generic features. Given the ever highly interconnected nature of the global economic system, a network dynamics approach may provide some key insights toward this goal. In this talk, we discuss how the connectivity patterns of the global economic system would affect the spreading...
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  8. Dr Verónica Ramenzoni (Max-Planck-Institute for the Psycholinguistics)
    07/04/2011, 16:10
    In recent years, research in the field of social interactions has focused on the exploration of the coordinative structures that substantiate joint task performance. Coordinative structures or synergies refer to online the soft-assembly of neuromuscular elements that function as a collective unit. Synergies exploit neuromotor redundancies to provide multiple, equivalent motor...
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  9. Dr Helena Buhr (Northwestern University)
    07/04/2011, 16:50
    We use a dataset of email communication to document the formation of social relationships between students in a prestigious MBA program. First, we analyze how new relationships form day by day during students' time in the program. Our dataset starts before students' arrival on campus and it offers an unique opportunity to understand the inception of a social network. Second, we examine...
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  10. Prof. Fredrik Liljeros (Stockholm University)
    07/04/2011, 17:30
    Sexually transmitted infections continue to be a severe health problem. In this talk I will present and discuss a variety of explanations that have been advanced on why this type of disease is so hard to eradicate, despite the fact that the contact by which it is spread is far less frequent than is the case with most other infectious diseases. We conclude that several processes and...
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  11. Prof. Aaron Clauset (University of Colorado)
    08/04/2011, 09:00
    Modular structures in complex networks can be extremely important for understanding the functional, dynamical, evolutionary and robustness properties of networks, and are widely believed to be ubiquitous in complex social, biological and technological networks. Most of the empirical evidence in support of the modular hypothesis, however, is indirect and derived from "community" or module...
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  12. Dr Martin Rosvall (Umeå University)
    08/04/2011, 09:40
    Ever since Aristotle, organization and classification have been cornerstones of science. In network science, categorization of nodes into modules with community-detection algorithms has proven indispensable to comprehending the structure of large integrated systems. But in real-world networks, the organization rarely is limited to two levels, and modular descriptions can only...
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  13. Dr Sune Lehmann (Technical University of Denmark)
    08/04/2011, 10:40
    We know that communities in networks often overlap such that nodes simultaneously belong to several groups. Additionally, many networks are known to possess hierarchical organization, where communities are recursively grouped into a hierarchical structure. However, when each and every node belongs to more than one group, a single global hierarchy of nodes cannot capture the relationships...
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  14. Dr Jevin West (University of Washington)
    08/04/2011, 11:20
    As Derek de Solla Price famously noted in 1965, the scientific literature forms a vast network. The nodes of this network are the millions of published articles, and they are linked to one another by citations and footnotes. This network grows dynamically and organically, doubling in size every ten to twenty years. It is within this growing network ecosystem that scholars conduct their...
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  15. Prof. Jordi Bascompte (Estación Biológica de Doñana, CSIC)
    08/04/2011, 13:30
    The mutualistic interactions between plants and the animals that pollinate them or disperse their seeds can form complex networks involving hundreds of species. These coevolutionary networks are highly heterogeneous, nested, and built upon weak and asymmetric links among species. Such general architectural patterns increase network robustness to random extinctions and maximize the number...
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  16. Dr Örjan Bodin (Stockholm University)
    08/04/2011, 14:10
    Abstract: When conceptualizing integrated social-ecological systems (SES), the modeling approaches commonly applied are often (a) based in ecology with social aspects added afterwards, or (b) based in social science with aspects of the natural environment added afterwards. So far there are few integrated conceptual modeling approaches that, from start, fully embrace the complex linkages...
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  17. Dr Sebastian Funk (Institute of Zoology)
    08/04/2011, 14:40
    Community structure is a ubiquitous feature of complex networks, and methods for its detection has gained much attention in recent years. Beyond the study social networks with well defined links, these methods can be generalised to operate on any dataset in which different entities are similar in one or more traits, and be used to identify meaningful groupings. Here, we describe the...
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  18. Dr Juyong Park (Kyung Hee University)
    08/04/2011, 15:10
    Exponential random graph theory is the complex network analog of the canonical ensemble theory from statistical physics. While it has been particularly successful in modeling networks with specified degree distributions, a naïve model of a clustered network using a graph Hamiltonian linear in the number of triangles has been shown to undergo an abrupt transition into an unrealistic phase...
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  19. Prof. Lada Adamic (University of Michigan)
    08/04/2011, 16:10
    Network time series can be used to track and predict the co-evolution of structure across different networks, and between a network's structure and its communicated content. We formulate a measure, temporal conductance, that captures how unexpected a particular network is given its past evolution. We find that structure in one network can not only correlate with the concurrent structure...
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  20. Prof. Kimmo Kaski (Aalto University)
    08/04/2011, 16:50
    Here we model the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short-range interactions as discussions between individuals and long-range interactions to describe the attitude to the overall mood of society. The...
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  21. Prof. Albert-László Barabási (Northeastern University)
    08/04/2011, 17:30
    The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. Here we develop analytical tools to study the controllability of an arbitrary complex directed...
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  22. Dr Thilo Gross (Max-Planck-Institute for the Physics of complex systems)
    09/04/2011, 09:00
    We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively, and independently adapt the amount of resources allocated to each of their collaborations in order to maximize the obtained payoff. We show analytically that the...
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  23. Prof. Sergey Dorogovtsev (University of Aveiro)
    09/04/2011, 09:40
    Until recently, the percolation phase transitions were believed to be continuous, however, in 2009, a remarkably different, discontinuous phase transition was reported in a new so-called "explosive percolation" problem. Each new link in this problem is established by a specific optimization process. We develop the exact theory of this phenomenon and explain its nature. Applying strict...
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  24. Roberta Sinatra (University of Catania)
    09/04/2011, 10:40
    There are many examples in biology, in linguistics and in the theory of dynamical systems, where information resides and has to be extracted from corpora of raw data consisting in sequences of symbols. For instance, a written text in English or in another language is a collection of sentences, each sentence being a sequence of the letters from a given alphabet. Not all sequences of...
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  25. Dr Vincenzo Nicosia
    09/04/2011, 11:10
    Many centrality measures have been proposed in the last decade to assess the relative importance of vertices in a complex network and to identify the role played by each node in the network. Finding important nodes is useful to estimate the potential damage that can be inflicted to the structure of a network by removing particular nodes. In this letter we show that it is always...
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  26. Prof. Beom Jun Kim (Sungkyunkwan University)
    09/04/2011, 11:40
    We explore the synchronization behavior in the interdependent system, where the 1D network is ferromagnetically intercoupled to the Watts-Strogatz (WS) small-world network. In the absence of the internetwork coupling, the former network is well known not to exhibit the synchronized phase at any finite coupling strength, whereas the latter displays the mean-field transition. Through an...
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  27. Dr Edith Ngai (Uppsala University)
    09/04/2011, 13:40
    With the popularity and advancements of smart phones, mobile users can interact with the sensing facilities and exchange information with other wireless devices in the environment by short range communications. Opportunistic exchange has recently been suggested in similar contexts; yet we show strong evidence that, in our application, opportunistic exchange would lead to insufficient...
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  28. Dr Bo Söderberg (Lund University)
    09/04/2011, 14:10
    Certain classes of random graphs can be derived as the Feynman graphs for simple quantum theories, with a statistical weight for each graph being given by the value of the corresponding Feynman graph. Such models of random graphs are closely related to a previously considered random graph model, known as CDRG, or Colored Degree-driven Random Graphs, where vertices are randomly equipped...
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  29. Prof. Vito Latora (University of Catania)
    09/04/2011, 14:50
    Random walks are the simplest way to explore a graph. In this talk we will discuss some of the properties of random walks (such as equilibrium distributions, entropy rates, and mean first-passage times) which might have relevant applications to study traffic fluctuations in the Internet, to design optimal diffusion processes on correlated or uncorrelated networks, or to achieve the...
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  30. Dr Kwang-Il Goh (Korea University)
    Persistent recurrence of global economic crises throughout economic history calls for understanding of their generic features. Given the ever highly interconnected nature of the global economic system, a network dynamics approach may provide some key insights toward this goal. In this talk, we discuss how the connectivity patterns of the global economic system would affect the spreading...
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  31. Dr Birgitte Freiesleben de Blasio (University of Oslo)
    Preferential attachment is a popular generative mechanism to explain the widespread observation of power law-distributed networks. An alternative explanation for the phenomenon is a randomly grown network with large individual variation in growth rates among the nodes (frailty). We derive analytically the distribution of individual rates, which will reproduce the connectivity...
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  32. Dr Birgitte Freiesleben de Blasio (Oslo University)
  33. Dr Petter Holme (Coputational Biology), Prof. Petter Minnhagen (Umeå University)